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We implemented least absolute shrinkage and selection operator (LASSO) regression to evaluate gene effects in genome-wide association studies (GWAS) of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as  MACROD2 ,  SORCS2 ,  GRIN2B ,  MAGI2 ,  NPAS3 ,  CLSTN2 ,  GABRG3 ,  NRXN3 ,  PRKAG2 ,  GAS7 ,  RBFOX1 ,  ADARB2 ,  CHD4 , and  CDH13 . The top genes we identified with this method also displayed significant and widespread  post hoc  effects on voxelwise, tensor-based morphometry (TBM) maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as  MACROD2 . We were able to successfully replicate the effect of the  MACROD2  gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8 ± 2.2 SD years). Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.

Discovery and replication of gene influences on brain structure using LASSO regression